Chaos and complexity
A system is described as complex when variables are interdependent: when changing one has a knock-on effect that changes others. This can result in a system becoming unstable, small changes bringing about sudden and unpredictable wholesale change. The system can oscillate wildly or settle down into a different steady state.
Weather is complex, so are business or competitive environments. They are unpredictable. Difficult or impossible to control.
With the advent of powerful computers in the 1960's, complex systems could be modeled and studied. Out of these studies, patterns emerged in the form of fractals. These showed that by altering the variables of a complex system it could be made to switch between a number of steady states. These steady states became known as 'strange attractors' and the strategic use of this knowledge has become known as 'Chaos Theory'.
It then became apparent that nature was making use of this phenomenon in its evolutionary strategy. By changing the variables of a complex system (a biological organism) in a variety of different ways, it could selectively proceed through a sequence of different steady states towards increased organization and efficiency. It is this strategy that causes species and ecosystems to become increasingly more organized and efficient.
This same strategy can be used in complex business environments like the Web. There is no planning or prediction involved. All it takes is to engineer a highly adaptable infrastructure. This can then be used to create many small changes and take advantage of any favorable outcomes that emerge.
This is the way nature does it - with considerable success. And we can copy this strategy.
The philosophy and mind-set for this approach is totally at odds with conventional business strategies that seek to bring about order and control. Instead of trying to enforce order onto an erratic and unpredictable environment, chaos theory provides the conceptual models that allow us to take advantage of change, capitalizing on favorable emergent developments.
Stigmergic systems are based upon these principles.
There are several articles in the 'References' section that describe complexity, chaos and attractors. The article "Controlling complexity" in the 'Technical notes' section describes how these concepts are applied to stigmergic systems.